Cost-Effective Active Learning for Deep Image Classification

• Published in: IEEE transactions on circuits and systems for video technology Vol. 27; no. 12; pp. 2591 - 2600
• Main Authors: Wang, Keze, Zhang, Dongyu, Li, Ya, Zhang, Ruimao, Lin, Liang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Active learning; Active learning (AL); Annotations; Artificial neural networks; Classification; Classifiers; deep neural nets; Face recognition; Image classification; incremental learning; Learning; Learning systems; Machine learning; Measurement uncertainty; Neural networks; Object recognition; Representations; Training; Uncertainty; Visualization

Recent successes in learning-based image classification, however, heavily rely on the large number of annotated training samples, which may require considerable human effort. In this paper, we propose a novel active learning (AL) framework, which is capable of building a competitive classifier with...